3 ms·

Not an expert -- would this be a result of training data doing a much better job isolating the subject vs a real world photo that may have other plants in the s

by lojack 9y ago

Not an expert -- would this be a result of training data doing a much better job isolating the subject vs a real world photo that may have other plants in the scene? Not that this is a solution in all cases, but is it possible your results would have improved with better real world pictures?

roystonvassey 9y ago
Likely but the whole point of 'AI' is that it should be able to identify flowers that don't look like what it's seen before. If not, it's just a huge lookup table that's like a memory repository. This is, of course, a critical challenge in data science and is definitely not a trivial one to solve.
- lojack 9y ago
  In some cases these are the goals, but dharma1 said the goal was to identify plant disease. If you can improve your results by taking better pictures then it becomes a tradeoff between training someone to take pictures and training someone to identify plant disease. I think we have a tendency to treat AI as a silver bullet when we should be treating it as a tool we can use to help augment what we're already doing.
pvaldes 9y ago
Not necessarily improved, because in real world photos you can have what I would baptise as "the voynich effect". Plants in Voynich manuscript aren't real, can't even be classified in a family, but strangely still look familiar to us because they are "frankenplants". You can have exactly the same problem in photos of wild plants. It only takes the leaves of a climber growing over the flowers of other plant, or different flowers and fruits mixed together; and you'll have a new species. A very tricky one to identify. After scratching the head for a while humans can sense that something is wrong... machines normally can't see the problem. An (in)famous case is the photo of two juxtaposed black people arranged casually in a geometry that was tagged by the machine as 'gorilla'.

by lojack 9y ago

roystonvassey 9y ago

Likely but the whole point of 'AI' is that it should be able to identify flowers that don't look like what it's seen before. If not, it's just a huge lookup table that's like a memory repository. This is, of course, a critical challenge in data science and is definitely not a trivial one to solve.

lojack 9y ago
In some cases these are the goals, but dharma1 said the goal was to identify plant disease. If you can improve your results by taking better pictures then it becomes a tradeoff between training someone to take pictures and training someone to identify plant disease. I think we have a tendency to treat AI as a silver bullet when we should be treating it as a tool we can use to help augment what we're already doing.

pvaldes 9y ago

Not necessarily improved, because in real world photos you can have what I would baptise as "the voynich effect". Plants in Voynich manuscript aren't real, can't even be classified in a family, but strangely still look familiar to us because they are "frankenplants". You can have exactly the same problem in photos of wild plants. It only takes the leaves of a climber growing over the flowers of other plant, or different flowers and fruits mixed together; and you'll have a new species. A very tricky one to identify. After scratching the head for a while humans can sense that something is wrong... machines normally can't see the problem. An (in)famous case is the photo of two juxtaposed black people arranged casually in a geometry that was tagged by the machine as 'gorilla'.